Evidence map›Paper›PMID 28152521›Full record

ArticleOncotarget2017

LncSubpathway: a novel approach for identifying dysfunctional subpathways associated with risk lncRNAs by integrating lncRNA and mRNA expression profiles and pathway topologies.

Yanjun Xu, Feng Li, Tan Wu, Yingqi Xu, Haixiu Yang, Qun Dong, Meiyu Zheng, Desi Shang, Chunlong Zhang, Yunpeng Zhang and 1 more

Abstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. The functions and unique features of long intergenic non-coding RNA.Nature reviews. Molecular cell biology · 2018
    Review
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Yanjun XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Feng LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Tan WuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yingqi XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Haixiu YangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Qun DongCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Meiyu ZhengCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Desi ShangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Chunlong ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yunpeng ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Xia LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs) play important roles in various biological processes, including the development of many diseases. Pathway analysis is a valuable aid for understanding the cellular functions of these transcripts. We have developed and characterized LncSubpathway, a novel method that integrates lncRNA and protein coding gene (PCG) expression with interactome data to identify disease risk subpathways that functionally associated with risk lncRNAs. LncSubpathway identifies the most relevance regions which are related with risk lncRNA set and implicated with study conditions through simultaneously considering the dysregulation extent of lncRNAs, PCGs and their correlations. Simulation studies demonstrated that the sensitivity and false positive rates of LncSubpathway were within acceptable ranges, and that LncSubpathway could accurately identify dysregulated regions that related with disease risk lncRNAs within pathways. When LncSubpathway was applied to colorectal carcinoma and breast cancer subtype datasets, it identified cancer type- and breast cancer subtype-related meaningful subpathways. Further, analysis of its robustness and reproducibility indicated that LncSubpathway was a reliable means of identifying subpathways that functionally associated with lncRNAs. LncSubpathway is freely available at http://www.bio-bigdata.com/lncSubpathway/.

Indexed as

AlgorithmsBreast NeoplasmsColorectal NeoplasmsComputational BiologyComputer SimulationGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansInternetReproducibility of ResultsRisk FactorsRNA, Long NoncodingRNA, MessengerSignal TransductionRNA, Long NoncodingRNA, MessengerlncRNAnetworkpathway topologiessubpathway

Identifiers

PMID28152521
PMCPMC5362499

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.